In #JPM2023 news, $QSI Quantum-SI also presented on January 12, 2023. The company launched their Platinum protein sequencer a few weeks ago.
The technology is not too dissimilar from the DNA sequencing Ion Torrent technology: a dense array of wells capture the proteins, then single molecule sequencing takes place independently in each well, and the different reactions for the different aminoacids are captured.
These different amino acids can include post-translational modifications (PTMs) which are common in most mammals and it's fair to say that they are little understood compared to fields such as genomics or transcriptomics.
Compared to the traditional Mass Spectrometry approach, where signals from small peptides, constituents of the sample proteins, are matched against a large database of peptides that have been seen before, the $QSI Quantum-SI approach is truly "de novo".
Quantum-SI are not alone in this cohort of new companies encompassing different methods in what we can call #NextGenerationProteomicsSequencing (NGPS), and others like Encodia and Erisyon are putting together de novo protein sequencers with alternative tech.
The rest of the companies in the list, such as $SLGC Somalogic, $OLK Olink, $NAUT Nautilus or $QTRX Quanterix are working on high-throughput identification methods, sometimes limited to small panels.
Quantum-SI is partnering with Aviva Systems Biology and Vizit to further delve into the full spectrum of analyzable proteins, and have the tools to understand these in the context of diseases or drug mechanisms-of-action.
Since the instrument is not expensive, there will be labs that may want to try it out. One example user case the company put in a slide deck is the following: you are producing some protein, purify it, run a gel, and there are several bands in the gel. Which one is your
purified protein, and what's in the other bands?
It sounds like a simple question, and there may be very simple legitimate ways to get to the answer with Mass Spec approaches, but undoubtedly, many will want to give Quantum-SI Platinum instrument and methods a try now.
On library prep at #Nanoporeconf, a description for PCR-free methods showing the difference between ligation (max output) and rapid mode (10minutes, minimal lab equipment needed). Ultralong reads (ULR) also enabled, all Kit14.
Rapid ULR. Current record is about 4 megabases.
PCR expansion kits enable the use of samples with low input amount.
I did a deep dive on the different workflow management (WFM) tools for #Bioinformatics Data Analysis a few years ago, and since then there have been a few extra entrants in this segment, still mostly concentrated in serving the Next-Generation Sequencing field.
A few years ago, there were two communities dominating the open-source WFM ecosystem in NextFlow and SnakeMake, and two platforms dominating the the commercial offerings in DNAnexus and Illumina BaseSpace.
Since then, a company out of the founders of Nextflow has started offering enterprise support for Nextflow workflows in the cloud: Seqera Labs. They offer the extra level of support that some organizations require to run Nextflow on their Data Analysis setups.
More interesting Next-Generation Sequencing knowledge in the ASeq Discord channel (by @new299). Illumina patterned flowcells and the etching process to "print" the wells into the flowcell. Could be down to 350nm diameter for some flowcell configurations now.
If I remember correctly, Illumina started with a 600nm diameter for the patterned flowcell, in the HiSeq X and then later on in the evolution of the platform that used these patterned flowcells.
They then said to have gone down to 500nm, and what you are showing seems to indicate that it's at 350nm now, at least for the NextSeq 2000? I am not sure if they claimed that for NovaSeq X?
There have been some acquisitions in #CancerDiagnostics and #CancerScreening recently, some of which signify a trend towards consolidation that is worth describing:
$A Agilent is moving towards some more vertical integration in Cancer Dx and Cancer screening
by recently acquiring both announcing a partnership with Akoya Bio and announcing the acquisition of Avida Biomed.
Some may ask: isn’t $A Agilent too small to go into this field? Would they be able to compete against $ILMN Illumina/GrailBio or $GH Guardant Health or $EXAS Exact Sciences?
It is likely that as Spatial Biology tools become more robust and user-friendly, they will become increasingly popular and widely adopted in the scientific community.
This may lead to a shift in the balance between single-cell and Spatial Biology approaches, with the latter eventually becoming more prevalent.
Additionally, as more and more datasets are generated using Spatial Biology techniques, the field of Machine Learning and Artificial Intelligence will likely play an increasingly important role in analysing and interpreting this data.